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基于社区的调查和干预研究设计的方差成分和组内相关性:来自1994年英格兰健康调查的数据

Components of variance and intraclass correlations for the design of community-based surveys and intervention studies: data from the Health Survey for England 1994.

作者信息

Gulliford M C, Ukoumunne O C, Chinn S

机构信息

Department of Public Health Sciences, King's College London, United Kingdom.

出版信息

Am J Epidemiol. 1999 May 1;149(9):876-83. doi: 10.1093/oxfordjournals.aje.a009904.

Abstract

The authors estimated components of variance and intraclass correlation coefficients (ICCs) to aid in the design of complex surveys and community intervention studies by analyzing data from the Health Survey for England 1994. This cross-sectional survey of English adults included data on a range of lifestyle risk factors and health outcomes. For the survey, households were sampled in 720 postal code sectors nested within 177 district health authorities and 14 regional health authorities. Study subjects were adults aged 16 years or more. ICCs and components of variance were estimated from a nested random-effects analysis of variance. Results are presented at the district health authority, postal code sector, and household levels. Between-cluster variation was evident at each level of clustering. In these data, ICCs were inversely related to cluster size, but design effects could be substantial when the cluster size was large. Most ICCs were below 0.01 at the district health authority level, and they were mostly below 0.05 at the postal code sector level. At the household level, many ICCs were in the range of 0.0-0.3. These data may provide useful information for the design of epidemiologic studies in which the units sampled or allocated range in size from households to large administrative areas.

摘要

作者通过分析1994年英格兰健康调查的数据,估计了方差成分和组内相关系数(ICC),以辅助复杂调查和社区干预研究的设计。这项针对英国成年人的横断面调查涵盖了一系列生活方式风险因素和健康结果的数据。在该调查中,家庭样本来自177个地区卫生当局和14个区域卫生当局下辖的720个邮政编码区。研究对象为16岁及以上的成年人。ICC和方差成分通过嵌套随机效应方差分析进行估计。结果在地区卫生当局、邮政编码区和家庭层面呈现。在每个聚类层面,聚类间变异均很明显。在这些数据中,ICC与聚类大小呈负相关,但当聚类规模较大时,设计效应可能很大。在地区卫生当局层面,大多数ICC低于0.01,在邮政编码区层面大多低于0.05。在家庭层面,许多ICC在0.0 - 0.3范围内。这些数据可能为流行病学研究的设计提供有用信息,此类研究中抽样或分配的单位规模从家庭到大型行政区不等。

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